Fundamentals of interactive computer graphics
Fundamentals of interactive computer graphics
Document Image Decoding Using Markov Source Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keyword Spotting in Poorly Printed Documents using Pseudo 2-D Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Planar Object Classes
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Probablistic Affine Invariants for Recognition
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Language Independent Word Spotting in Scanned Documents
ICADL 08 Proceedings of the 11th International Conference on Asian Digital Libraries: Universal and Ubiquitous Access to Information
Keyword Spotting Techniques for Sanskrit Documents
Sanskrit Computational Linguistics
Expert Systems with Applications: An International Journal
The emergence of visual categories: a computational perspective
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Context, Computation, and Optimal ROC Performance in Hierarchical Models
International Journal of Computer Vision
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Different instances of a handwritten word consist of the same basic features (humps, cusps, crossings, etc.) arranged in a deformable spatial pattern. Thus, keywords in cursive text can be detected by looking for the appropriate features in the "correct" spatial configuration. A keyword can be modeled hierarchically as a set of word fragments, each of which consists of lower level features. To allow flexibility, the spatial configuration of keypoints within a fragment is modeled using a Dryden-Mardia (DM) probability density over the shape of the configuration. In a writer-dependent test on a transcription of the Declaration of Independence (~1300 words, ~7500 characters), the method detected all eleven instances of the keyword "government" with only four false positives.